Methods: Coding took place in three sessions; each run by different groups of students. First, students were trained coding by developing criteria for coding (1=low status to 5=high status) and practicing coding on pictures of cars in a powerpoint. An example of an “1” would be an old, beat-up Chevrolet; an example of a “2” would be a Ford or Honda with some age and wear and tear; an example of “3” be a relatively new Ford or Honda; an example of a “4” would be a new Toyota Prius or Volkswagen; an example of “5” would be a new Mercedes-Benz, Range Rover or Porsche. Two of the sessions took place during the day; the other took place at night. A confederate would look to cross the street using the crosswalk while a car was approaching the crosswalk. The car was then coded for its status (1=low status to 5=high status) by two different coders (interrater reliability r=.754) and for whether it stopped for the pedestrian or not (0=stopped, 1=did not stop). The gender of the driver was also recorded (1=male, 2=female; 140 male, 100 female).

Results: A Pearson correlation was used to determine the relationship between car status and whether a car stops for a pedestrian at crosswalks, r(240)=.11, p = .088. A graph of the percent of cars that did not stop for the pedestrian vs. car status can be seen in the figure. There was a curvilinear relationship between car status (the average of the two raters) and breaking the law. The pattern suggests that the status-lawbreaking relationship is consistent with the original article up until status =4, then drops off. Note that there were only 8 cars rated in the 5th level of the status variable.

Any Known Methodological Differences (between original and present study)?

No known differences.

Email of Investigator

Name of individuals who actually carried out the project

All investigators recorded and analyzed the data.

Location of Project

Academy Street near Perkins Student Center, University of Delaware, Newark, DE; Main Street near Grotto Pizza and North Green, University of Delaware, Newark, DE; Intersection of West Main St. and South Main St. (two crosswalks), University of Delaware

Characteristics of Subjects (subject pool, paid, etc.)

OtherCar drivers driving through streets around the University of Delaware.

Where did these subjects reside?

United States

Was this a Class Project?

Yes

Further Details of Results as pdf

Additional Comments

Email of Original Investigator

Quantitive Information

The data below come from our replication study; these values can be compared to Piff et al,.’s Figure 1, Panel B.
Proportion of cars that did not stop for pedestrians (Status ratings averaged over the two raters)
(Status 1 or 1.5)= .222; N = 27; SE=.082
(Status 2 or 2.5)= .338; N = 65; SE=.059
(Status 3 or 3.5)= .462; N = 117 ; SE=.046
(Status 4 or 4.5)= .435; N = 23; SE=.106
(Status 5) = .250 ; N = 8; SE=.164
Our correlation of r = .11 is in the same direction of Piff et al.’s relationship.
The original relationship they observed was quantified at b = 0.39. In their analysis, they controlled for driver sex and age. We could not compute the same analyses because we recorded only driver sex, not age.

I have complied with ethical standards for experimentation on human beings and, if necessary, have
obtained appropriate permission from an Institutional Review Board or other oversight group.